POSTAR2 is a user-friendly database, which provides a platform to connect protein-RNA interactions with multi-layer information of post-transcriptional regulation, as well as a translation landscape of RNAs across various tissues, cell lines and conditions. Moreover, it’s helpful for biologists to generate novel hypotheses about the regulatory mechanisms of phenotypes and diseases.

(4) Target gene exp.level: a link to the bar chart of the gene expression values across different tissues or cell lines.

(5) Binding site records: a link to the table of all binding sites of the RBP and the target genes. You can also see details about transcript, genomic context, tissue type and more information by clicking on the “Details” button.

1.2.3 Enriched Gene Ontologies of the RBP targets

Table view of the GO terms enriched in the query RBP’s set of target genes.

Here is an example showing how to search the translation landscape of one gene in translatome module and read the results.

Input:

Firstly, you should select a species: human, mouse, fly, worm, Arabidopsis or yeast and enter a gene name(i.e., TP53). Then you should choose “Search a Gene or lncRNA”.

Result:

3.1 TP53 translatome summary

This section is the general summary of the selected gene. It includes:

(1) In the ORF annotation summary, all ORFs that are included within the gene. Based on given annotation, ORFs are further categorized into different groups. The number on the top of each bar represents the number of ORFs falling in the corresponding ORF category.

The explanation of different ORF categories is illustrated as following:

Annotated ORFs(aORFs): ORFs that are annotated by reference. aORFs are colored in green in the diagram.

Extended ORFs/Truncated ORFs: ORFs that are of the same stop codon as aORFs but have different translation initiation sites.

Upstream ORFs(uORFs)/downstream ORFs(dORFs): ORFs that are located upstream/downstream of one aORF.

Internal overlapped ORFs: ORFs that are within different reading frame as the aORFs but have overlapping with the aORFs.

Unannotated ORFs: ORFs without any annotation.

(2) ORF density across samples shows the Ribo-seq density of each ORF across different samples.

3.2 Annotated ORFs of TP53

Table view of all aORFs for the query gene(i.e.,TP53). It includes:

(1) ORFID: ORFID is named based on the composition of transcript, reading frame, translation start sites and stop sites.

(2) Transcript

(3) Category

(4) Reading frame: Reading frame is counted based on the relative distance between transcript start sites(TSS).

(5) Start position: start position is numbered based on the relative position of translation initiation sites along the transcript.

(6) End position: end position refers to the last nucleotide of ORF along the transcript.

(7) Length: ORF length

3.3 Extended/Truncated ORFs of TP53

3.4 Other ORFs of TP53

3.5 Detail information for a specific ORF:

For each ORF, a detail characterization is provided by clicking on the link of this ORF from which the server will automatically demonstrate the translation efficiency(TE), translation density and the potential of active translation of this ORF.

(1) Translation efficiency(TE):

This table summarizes TE calculated based on either original signal of Ribo-seq or denoised periodic signal of Ribo-seq across different samples. TE is defined as the ratio between Ribo-seq RPKM and RNA-seq RPKM(1).

(2) Translation density:

This table summarizes Ribo-seq reads density of selected ORF across different samples. Translation density is defined as the average reads intensity within the ORF.

(3) Identify translated region:

In this section, we used four published methods, i.e., RiboWave, RiboTaper(2), ORFscore(3) and RibORF(4). The number on the top of each bar represents the calculated output for each method among different samples. For RiboWave and RiboTaper, the output is presented in the format of -1*log(p value) in which p value < 0.05(or -1*log(p value) > 2.996) indicates the potential of active translation. Similarly, the output of ORFscore requires its value higher than 6.044 to indicate active translation and RibORF requires its score higher than 0.7.

(4) Signal track demonstration:

Finally, we also provide the option to output the signal track of Ribo-seq data for either original signal or the denoised periodic footprint. In this part, user can specify multiple datasets at the same time. The signal track is presented along the transcript with the studied ORF highlighted in green on the bottom. Ribo-seq signals are colored in blue.